NONLINEAR FEATURE EXTRACTION USING FISHER CRITERION-Reference-Cited by-同舟云学术

NONLINEAR FEATURE EXTRACTION USING FISHER CRITERION

Published:2008-09 Issue:06 Volume:22 Page:1089-1119
ISSN:0218-0014
Container-title:International Journal of Pattern Recognition and Artificial Intelligence
language:en
Short-container-title:Int. J. Patt. Recogn. Artif. Intell.

Author:

BUSTOS MATÍAS A.¹,DUARTE-MERMOUD MANUEL A.¹,BELTRÁN NICOLÁS H.¹

Affiliation:

1. Electrical Engineering Department, University of Chile, Av. Tupper 2007, Casilla 412-3, Santiago, Chile

Abstract

In this paper the problem of nonlinear feature extraction based on the optimization of the Fisher criterion is analyzed. A new nonlinear feature extraction method is proposed. The method does not make use of numerical algorithms and it has an analytical (closed-form) solution. Moreover, no assumptions on the class probability distribution functions are imposed. The proposed method is applied to some standard pattern recognition problems and compared with other classical methodologies already proposed in the literature. The performance of the proposed method turned out to be superior when compared with the other methods studied.

Publisher

World Scientific Pub Co Pte Lt

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Software

Link

https://www.worldscientific.com/doi/pdf/10.1142/S0218001408006715

Reference28 articles.

1. Feature reduction for classification of multidimensional data

2. CANONICAL VARIATE ANALYSIS-A GENERAL MODEL FORMULATION

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